# europe_spai020 - Penota - Breitenmoser Tree Ring Chronology Data #----------------------------------------------------------------------- # World Data Center for Paleoclimatology, Boulder # and # NOAA Paleoclimatology Program #----------------------------------------------------------------------- # NOTE: Please cite Publication, and Online_Resource and date accessed when using these data. # If there is no publication information, please cite Investigators, Title, and Online_Resource and date accessed. # # # Online_Resource: # # Online_Resource: https://www.ncdc.noaa.gov/paleo/study/24611 # # Original_Source_URL:https://www.ncdc.noaa.gov/paleo/study/3255 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_spai020 - Penota - Breitenmoser Tree Ring Chronology Data #-------------------- # Investigators # Investigators: Breitenmoser, P.; Bronnimann, S.; Frank, D. #-------------------- # Description_and_Notes # Description: Data from Breitenmoser 2014 Journal of past Climate supplementary, see publication for ARSTAN standardization details #-------------------- # Publication # Authors: Breitenmoser, P.; Bronnimann, S.; Frank, D. # Published_Date_or_Year: 2014-03-11 # Published_Title: Forward modelling of tree-ring width and comparison with a global network of tree-ring chronologies # Journal_Name: Climate of the Past # Volume: 10 # Edition: # Issue: # Pages: 437-449 # DOI: 10.5194/cp-10-437-2014 # Online_Resource: www.clim-past.net/10/437/2014/ # Full_Citation: # Abstract: We investigate relationships between climate and tree-ring data on a global scale using the process-based Vaganov–Shashkin Lite (VSL) forward model of tree-ring width formation. The VSL model requires as inputs only latitude, monthly mean temperature, and monthly accumulated precipitation. Hence, this simple, process-based model enables ring-width simulation at any location where monthly climate records exist. In this study, we analyse the growth response of simulated tree rings to monthly climate conditions obtained from the CRU TS3.1 data set back to 1901. Our key aims are (a) to assess the VSL model performance by examining the relations between simulated and observed growth at 2287 globally distributed sites, (b) indentify optimal growth parameters found during the model calibration, and (c) to evaluate the potential of the VSL model as an observation operator for data-assimilation-based reconstructions of climate from tree-ring width. The assessment of the growth-onset threshold temperature of approximately 4–6 C for most sites and species using a Bayesian estimation approach complements other studies on the lower temperature limits where plant growth may be sustained. Our results suggest that the VSL model skilfully simulates site level treering series in response to climate forcing for a wide range of environmental conditions and species. Spatial aggregation of the tree-ring chronologies to reduce non-climatic noise at the site level yielded notable improvements in the coherence between modelled and actual growth. The resulting distinct and coherent patterns of significant relationships between the aggregated and simulated series further demonstrate the VSL model’s ability to skilfully capture the climatic signal contained in tree-ring series. Finally, we propose that the VSL model can be used as an observation operator in data assimilation approaches to reconstruct past climate. #-------------------- # Authors: Anderson, D.M., Tardif, R., Horlick, K., Erb, M.P., Hakim, G.J., Noone, D., Perkins, W.A., and E. Steig # Published_Date_or_Year: 2018 # Published_Title: Additions to the last millennium reanalysis multi-proxy database # Journal_Name: Data Science Journal # Volume: # Edition: # Issue: # Pages: # Report_Number: # DOI: # Online_Resource: # Full_Citation: Anderson, D.M., Tardif, R., Horlick, K., Erb, M.P., Hakim, G., J., Noone, D., Perkins, W.A., and E. Steig, submitted. Additions to the last millennium reanalysis multi-proxy database. Data Science Journal. # Abstract: Progress in paleoclimatology increasingly occurs via data syntheses. We describe additions to a collection prepared for use in paleoclimate state estimation, specifically the Last Millennium Reanalysis (LMR). The 2290 additional series include 2152 tree ring chronologies and 138 other series. They supplement the collection used previously and together form a database titled LMRdb 1.0.0. The additional data draws from lake core, ice core, coral, speleothem, and tree ring archives, using published data primarily from the NOAA Paleoclimatology archive and a set of tree ring width chronologies standardized from raw International Tree Ring Data Bank ring width series. In contrast to many previous paleo compilations, the data were not selected (screened) on the basis of their environmental correlation, multi-century length, or other attributes. The inclusion of proxies sensitive to moisture and other environmental variables expands their use in data assimilation. A preliminary calibration using linear regression with mean annual temperature reveals characteristics of the proxy series and their relationship to temperature, as well as the noise and error characteristics of the records. The additional records are structured as individual files in the NOAA Paleoclimatology format and archived at NOAA Paleoclimatology (Anderson et al. 2018) and will continue to be improved and expanded as part of the LMR Project. The additions represent a four-fold increase in the number of records available for assimilation, provide expanded geographic coverage, and add additional proxy variables. Applications include data assimilation, proxy system model development, and paleoclimate reconstruction using climate field reconstruction and other methods. #------------------ # Funding_Agency # Funding_Agency_Name: Swiss National Science Foundation # Grant: #-------------------- # Funding_Agency_Name: National Science Foundation # Grant:AGS-1304263 # Funding_Agency_Name: National Oceanic and Atmospheric Administration # Grant:NA14OAR4310176 #------------------ # Site_Information # Site_Name: Penota # Location: # Country: Spain # Northernmost_Latitude: 40.67 # Southernmost_Latitude: 40.67 # Easternmost_Longitude: -0.33 # Westernmost_Longitude: -0.33 # Elevation: 1650 m #-------------------- # Data_Collection # Collection_Name: europe_spai020B # Earliest_Year: 1805 # Most_Recent_Year: 1991 # Time_Unit: y_ad # Core_Length: # Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"M", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"5.12460777694","T2":"16.6561493678","M1":"0.0221919671891","M2":"0.48552444562"}} #-------------------- # Species # Species_Name: Scots pine # Species_Code: PISY #-------------------- # Chronology: # # # #-------------------- # Variables # # Data variables follow that are preceded by ## in columns one and two. # Data line variables format: Variables list, one per line, shortname-tab-longname-tab-longname components (9 components: what, material, error, units, seasonality, archive, detail, method, C or N for Character or Numeric data) # ##age age, , ,years AD, , , , ,N ##trsgi tree ring standardized growth index, tree ring, ,percent relative to mean growth, , Tree Rings, , ,N # #-------------------- # Data: # Data lines follow (have no #) # Data line format - tab-delimited text, variable short name as header # Missing Values: nan # age trsgi 1805 0.923 1806 0.587 1807 0.895 1808 0.803 1809 0.807 1810 0.821 1811 1.128 1812 0.968 1813 1.067 1814 1.077 1815 0.968 1816 0.848 1817 0.827 1818 0.751 1819 0.768 1820 0.814 1821 0.722 1822 0.838 1823 0.931 1824 0.734 1825 0.995 1826 1.042 1827 0.915 1828 0.84 1829 0.78 1830 1.055 1831 0.977 1832 0.721 1833 0.66 1834 0.988 1835 1.374 1836 1.447 1837 1.23 1838 0.935 1839 1.095 1840 0.991 1841 1.291 1842 0.949 1843 1.292 1844 1.105 1845 1.013 1846 1.351 1847 1.316 1848 1.04 1849 1.171 1850 1.454 1851 0.93 1852 0.699 1853 0.99 1854 1.165 1855 0.731 1856 0.733 1857 0.968 1858 1.129 1859 1.029 1860 0.77 1861 0.695 1862 0.709 1863 0.817 1864 0.987 1865 0.772 1866 0.614 1867 0.856 1868 0.954 1869 1.011 1870 0.908 1871 1.028 1872 0.748 1873 0.555 1874 0.683 1875 0.875 1876 1.195 1877 1.022 1878 0.9 1879 0.559 1880 0.778 1881 0.688 1882 0.868 1883 0.72 1884 0.838 1885 0.906 1886 1.155 1887 0.903 1888 0.88 1889 0.78 1890 0.973 1891 0.833 1892 0.816 1893 1.146 1894 0.781 1895 0.842 1896 1.192 1897 1.183 1898 0.927 1899 0.989 1900 0.607 1901 0.955 1902 1.29 1903 1.589 1904 1.237 1905 1.203 1906 1.022 1907 1.184 1908 0.85 1909 0.922 1910 0.988 1911 0.886 1912 1.322 1913 1.115 1914 1.498 1915 1.249 1916 1.076 1917 0.932 1918 1.243 1919 0.986 1920 1.073 1921 0.857 1922 0.971 1923 1.256 1924 0.874 1925 1.102 1926 1.244 1927 0.94 1928 0.822 1929 1.004 1930 1.064 1931 1.13 1932 1.125 1933 1.309 1934 0.729 1935 0.673 1936 0.921 1937 1.216 1938 1.118 1939 0.751 1940 0.917 1941 0.563 1942 0.637 1943 0.852 1944 1.032 1945 0.944 1946 0.943 1947 1.128 1948 1.022 1949 0.951 1950 0.959 1951 0.647 1952 0.67 1953 0.844 1954 0.675 1955 1.054 1956 1.031 1957 0.999 1958 0.986 1959 1.405 1960 0.886 1961 0.998 1962 0.912 1963 0.701 1964 1.031 1965 0.871 1966 0.942 1967 1.014 1968 1.075 1969 0.88 1970 0.872 1971 1.084 1972 1.032 1973 0.971 1974 0.976 1975 1.058 1976 1.347 1977 1.377 1978 0.833 1979 0.842 1980 1.377 1981 1.183 1982 1.223 1983 1.386 1984 1.198 1985 1.239 1986 0.947 1987 1.064 1988 1.037 1989 1.153 1990 1.224 1991 0.862